>Yes it is. It is still exactly as simple as it sounds. If I’m doing math billions of times that doesn’t make the base process somehow more substantial. It’s still math, still a machine designed to predict the next token without being able to reason, meaning that yes, they are just fancy pattern-matching machines.

I find this argument even stranger. Every system can be reduced to its parts and made to sound trivial thereby. My brain is still just neurons firing. The world is just made up of atoms. Humans are just made up of cells.

>here’s actually a few commonly understood theories of existence that are generally accepted even by laypeople, like, “if I ask a sentient being how many Rs there are in the word ‘strawberry’ it should be able to use logic to determine that there are three and not two,” which is a test that generative AI frequently fails.

This shows that the author is not very curious because its easy to take the worst examples from the cheapest models and extrapolate. Its like asking a baby some questions and interpreting humanity's potential on that basis. What's the point of this?

> The questions leftists ask about AI are: does this improve my life? Does this improve my livelihood? So far, the answer for everyone who doesn’t stand to get rich off AI is no.

I'll spill the real tension here for all of you. There are people who really like their comfy jobs and have got attached to their routine. Their status, self worth and everything is attached to it. Anything that disrupts this routine is obviously worth opposing. Its quite easy to see how AI can make a person's life better - I have so many examples. But that's not what "leftists" care about - its about security of their job.

The rest of the article is pretty low quality and full of errors.

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iugtmkbdfil834 3 hours ago | parent | next [-]

<< This shows that the author is not very curious because its easy to take the worst examples from the cheapest models and extrapolate.

I find this line of reasoning compelling. Curiosity ( and trying to break things ) will get you a lot fun. The issue I find that people don't even try to break things ( in interesting ways ), but repeat common failure modes more as a gospel and not an observed experiment. The fun thing is that even the strawberry issue tells us more about the limitations of llms than not. In other words, that error is useful...

<< Their status, self worth and everything is attached to it. Anything that disrupts this routine is obviously worth opposing.

There is some of that for sure. Of all days, today I had my manager argue against use of AI for a use case that would affect his buddy's workflow. I let it go, because I am not sure what it actually means, but some resistance is based on 'what we have always done'.

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simianwords 3 hours ago | parent [-]

> The fun thing is that even the strawberry issue tells us more about the limitations of llms than not. In other words, that error is useful

That's a fair way to look at it - failure modes tell us something useful about the underlying system. In this case it tells us something about how LLM's work at the token level.

But if you go a step beyond that, you would realise that this problem is solved at a _general_ level with the reasoning models. GPT o1 was internally named strawberry as far as I remember. This would be a nice discussion to have but instead of shallow dismissal of AI as a technology with a failure mode that has been pretty much solved.

What really has not been solved is long context and continual learning (and world model stuff but I don't find that interesting).

	▲	iugtmkbdfil834 2 hours ago \| parent [-]
		<< What really has not been solved is long context and continual learning (and world model stuff but I don't find that interesting). I wonder about that. In a sense, the solution seems simple.. allow more context. One of the issues, based on progression of chatgpt models, was that too much context allowed for a much easier jailbreak and the fear most corporates have over that make me question the service. Don't get me wrong, I am not one of those people missing 4o for telling me "I love you". I do miss it its nerfed capability to go across all conversations. Working context is was made more narrow now. For a paid sub, that kind of limitation is annoying. My point is, I know there are some interesting trade-offs to be made ( mostly because I am navigating those on local inference machine ), but with all those data centers one would think, providers have enough power to solve that.. if they so chose.

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qsera 3 hours ago | parent | prev [-]

>Every system can be reduced to its parts and made to sound trivial thereby

But the trivialization does not come from being reduced to parts, but what parts you end up with.

It is like realizing the toy that seems to be able figure out a path around obstacles, cannot actually "see", but works by a clever arrangement of gears.

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simianwords 3 hours ago | parent [-]

>It is like realizing the toy that seems to be able figure out a path around obstacles, cannot actually see, but works by a clever arrangement of gears.

in this case can you come up with things that the toy can't do but a toy with eyes could have?

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ambicapter 2 hours ago | parent [-]

Yes? When you reverse-engineer a machine, it's obviously much easier to draw up an edge case it can't handle.

	▲	simianwords an hour ago \| parent [-]
		Can you draw up an edge case for LLMs?